Evidence map›Paper›PMID 36777309›Full record

ArticleHygiene and environmental health advances2022

How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state?

Wangjian Zhang, Xinlei Deng, Xiaobo X Romeiko, Kai Zhang, Scott C Sheridan, Jerald Brotzge, Howard H Chang, Eric K Stern, Zhijian Guo, Guanghui Dong and 3 more

Open access · diamondAbstract read
In one paragraph

Article in Hygiene and environmental health advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 37% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 7 institutions in 2 countries.

Wangjian ZhangDepartment of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Xinlei DengDepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA.
Xiaobo X RomeikoDepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA.
Kai ZhangDepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA.
Scott C SheridanDepartment of Geography, Kent State University, Kent, OH, USA.
Jerald BrotzgeNew York State Mesonet, College of Arts and Sciences, State University of New York, Rensselaer, NY, USA.
Howard H ChangDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
Eric K SternCollege of Emergency Preparedness, Homeland Security and Cybersecurity, State University of New York, Albany, NY, USA.
Zhijian GuoDepartment of Mathematics and Statistics, State University of New York, Albany, NY, USA.
Guanghui DongDepartment of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Ramune RelieneCancer Research Center, State University of New York, Rensselaer, NY, USA.
Yuantao HaoDepartment of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Shao LinDepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA.
University at Albany, State University of New York · USSun Yat-sen University · CNState University of New York · USAlbany State University · USEmory University · USKent State University · USUnited States Department of Homeland Security · US

Funding

Weather extremes, natural disasters, and health outcomes among vulnerable older adults: New improvements on exposure assessment, disparity identification, and risk communication strategiesR01AG070949 · NIA · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI LIN, SHAO · 2022 to 2025
$1.6M
Assess and Model the Health Effects, Population, and Infrastructural Vulnerabilities of Power OutageR15ES028000 · NIEHS · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI LIN, SHAO · 2018 to 2018
$444k
NCEH CDC HHS U01 EH000396NIA NIH HHS R01 AG070949NIEHS NIH HHS R15 ES028000
6 · The paper itself

Abstract

Background: Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State. Methods: We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees. Results: Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9-15.6%), population density (3.3-16.1%), per capita income (2.3-10.7%), and the density of public infrastructure (0.8-8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3-27.9%) and those with limited English (2.2-8.1%), the percent of sandy soil (6.5-11.8%), and average soil temperature (3.0-15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status. Conclusion: Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization.

Indexed as

Machine learningMultiple health outcomesNeighborhood environmentPower outageVulnerability

Identifiers

PMID36777309
PMCPMC9914544
OpenAlexW4309441581

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.